Some review platforms display how long reviewers used a product alongside their review. The authors investigate whether doing so translates to more helpful reviews. Using online reviews of video games from a video game platform and leveraging its unique playtime tracking feature, they find that the relationship between the amount of time playing a game before posting a review and the number of helpful votes the review receives follows a U-shaped curve, where shorter and longer playtimes correspond to more votes, while intermediate playtimes correspond to fewer votes. How displayed consumption time affects consumer expectations potentially explains this relationship. The less time reviewers spend consuming a product, the lower others’ expectations of review helpfulness may be and hence the more lenient their judgments. More consumption time may increase these expectations, but extensive consumption time could overcome this higher bar by signaling credibility. Moderation results related to reviewer experience signaling and review or product characteristics, as well as mediation results involving consumer-gifted review awards, help support this context-based expectations account. These results are robust to conditioning out review-, reviewer-, and game-level factors, sample matching, and other settings. The findings have implications for reducing the asymmetric information problem, managing expectations, and optimizing reviews.
AbellAnnikaMorganCarterRomeroMarisabel (2024), “The Power of a Star Rating: Differential Effects of Customer Rating Formats on Magnitude Perceptions and Consumer Reactions,” Journal of Marketing Research, 61 (6), 1041–57.
2.
AkbarabadiMinaHosseiniMonireh (2020), “Predicting the Helpfulness of Online Customer Reviews: The Role of Title Features,” International Journal of Market Research, 62 (3), 272–87.
3.
AlbaJoseph W.HutchinsonJ. Wesley (1987), “Dimensions of Consumer Expertise,” Journal of Consumer Research, 13 (4), 411–54.
CeylanGizemDiehlKristinProserpioDavide (2024), “Words Meet Photos: When and Why Photos Increase Review Helpfulness,” Journal of Marketing Research, 61 (1), 5–26.
7.
ChaseWilliam G.SimonHerbert A. (1973), “Perception in Chess,” Cognitive Psychology, 4 (1), 55–81.
8.
ChenPei-Yu (Sharon)HittLorin M. (2002), “Measuring Switching Costs and the Determinants of Customer Retention in Internet-Enabled Businesses: A Study of the Online Brokerage Industry,” Information Systems Research, 13 (3), 255–74.
9.
ChenYuboXieJinhong (2008), “Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix,” Management Science, 54 (3), 477–91.
10.
CraciunGeorgianaZhouWenqiShanZhe (2020), “Discrete Emotions Effects on Electronic Word-of-Mouth Helpfulness: The Moderating Role of Reviewer Gender and Contextual Emotional Tone,” Decision Support Systems, 130, 113226.
GhoseAnindyaIpeirotisPanos (2011), “Estimating the Helpfulness and Economic Impact of Product Reviews: Mining Text and Reviewer Characteristics,” IEEE Transactions on Knowledge and Data Engineering, 23 (10), 1498–512.
13.
GillyMary C.GrahamJohn L.WolfinbargerMary FinleyYaleLaura J. (1998), “A Dyadic Study of Interpersonal Information Search,” Journal of the Academy of Marketing Science, 26 (2), 83–100.
14.
HonnibalMatthewMontaniInesVan LandeghemSofieBoydAdriane (2020), “spaCy: Industrial-Strength Natural Language Processing in Python,” https://doi.org/10.5281/zenodo.1212303.
15.
HopeOle-KristianHuDanqiLuHai (2016), “The Benefits of Specific Risk-Factor Disclosures,” Review of Accounting Studies, 21, 1005–45.
16.
HoskinsJakeGopinathShyamVerhaalJ. CameronYazdaniElham (2021), “The Influence of the Online Community, Professional Critics, and Location Similarity on Review Ratings for Niche and Mainstream Brands,” Journal of the Academy of Marketing Science, 49, 1065–87.
17.
HuNanLiuLingZangJie Jennifer (2008), “Do Online Reviews Affect Product Sales? The Role of Reviewer Characteristics and Temporal Effects,” Information Technology Management, 9, 201–14.
18.
JohnsonKathy E.MervisCarolyn B. (1997), “Effects of Varying Levels of Expertise on the Basic Level of Categorization,” Journal of Experimental Psychology: General, 126 (3), 248–77.
19.
JungMiyeonRyuSunghanHanSang PilChoDaegon (2023), “Ask for Reviews at the Right Time: Evidence from Two Field Experiments,” Journal of Marketing, 87 (4), 528–49.
20.
KimJong MinHanJeongsoo (2022), “Impact of the Length of Stay at Hotels on Online Reviews,” International Journal of Contemporary Hospitality Management, 34 (4), 1249–69.
21.
KüblerRaoul V.LobschatLaraWelkeLinavan der MeijHugo (2024), “The Effect of Review Images on Review Helpfulness: A Contingency Approach,” Journal of Retailing, 100 (1), 5–23.
22.
LiLinyiGopinathShyamCarsonStephen J. (2022), “History Matters: The Impact of Online Customer Reviews Across Product Generations,” Management Science, 68 (5), 3878–903.
LudwigStephanHerhausenDennisGrewalDhruvBoveLilianaBenoitSabinede RuyterKoUrwinPeter (2022), “Communication in the Gig Economy: Buying and Selling in Online Freelance Marketplaces,” Journal of Marketing, 86 (4), 141–61.
25.
LutzBernhardPröllochsNicolasNeumannDirk (2022), “Are Longer Reviews Always More Helpful? Disentangling the Interplay Between Review Length and Line of Argumentation,” Journal of Business Research, 144, 888–901.
26.
MaheswaranDurairaj (1994), “Country of Origin as a Stereotype: Effects of Consumer Expertise and Attribute Strength on Product Evaluations,” Journal of Consumer Research, 21 (2), 354–65.
MetzgerMiriam J.FlanaginAndrew J.MeddersRyan B. (2010), “Social and Heuristic Approaches to Credibility Evaluation Online,” Journal of Communication, 60 (3), 413–39.
29.
MousaviJavadSinghSurendra N.ChatterjeePromotheshMastersTamara (2024), “Unveiling Stars: How Graphical Displays of Online Consumer Ratings Affect Consumer Perception and Judgment,” Journal of Marketing Research, 61 (2), 225–47.
30.
MukherjeeAsheshHoyerWayne D. (2001), “The Effect of Novel Attributes on Product Evaluation,” Journal of Consumer Research, 28 (3), 462–72.
31.
Ngo-YeThomas L.SinhaAtish P. (2014), “The Influence of Reviewer Engagement Characteristics on Online Review Helpfulness: A Text Regression Model,” Decision Support Systems, 61, 47–58.
32.
NguyenPeterWangXin (Shane)LiXiCotteJune (2021), “Reviewing Experts’ Restraint from Extremes and Its Impact on Service Providers,” Journal of Consumer Research, 47 (5), 654–74.
33.
PackardGrantBergerJonah (2017), “How Language Shapes Word of Mouth’s Impact,” Journal of Marketing Research, 54 (4), 572–88.
34.
ParryDouglas A.DavidsonBrittany I.SewallCraig J.R.FisherJacob T.MieczkowskiHannahQuintanaDaniel S. (2021), “A Systematic Review and Meta-Analysis of Discrepancies Between Logged and Self-Reported Digital Media Use,” Nature Human Behaviour, 5, 1535–47.
RitovIlana (2000), “The Role of Expectations in Comparisons,” Psychological Review, 107 (2), 345–57.
37.
RocklageMatthew D.FazioRussell H. (2020), “The Enhancing Versus Backfiring Effects of Positive Emotion in Consumer Reviews,” Journal of Marketing Research, 57 (2), 332–52.
38.
RocklageMatthew D.RuckerDerek D.NordgrenLoran F. (2021), “Emotionally Numb: Expertise Dulls Consumer Experience,” Journal of Consumer Research, 48 (3), 355–73.
39.
StangDavid J. (1975), “Effects of ‘Mere Exposure’ on Learning and Affect,” Journal of Personality and Social Psychology, 31 (1), 7–12.
40.
SunXinyuHanMaoxinFengJuan (2019), “Helpfulness of Online Reviews: Examining Review Informativeness and Classification Thresholds by Search Products and Experience Products,” Decision Support Systems, 124, 113099.
41.
SunderSarangKimKihyun HannahYorkstonEric A. (2019), “What Drives Herding Behavior in Online Ratings? The Role of Rater Experience, Product Portfolio, and Diverging Opinions,” Journal of Marketing, 83 (6), 93–112.
42.
TanYong-ChinChandukalaSandeep R.ReddySrinivas K. (2022), “Augmented Reality in Retail and Its Impact on Sale,” Journal of Marketing, 86 (1), 48–66.
43.
TodriVilmaAdamopoulosPanagiotis (Panos)AndrewsMichelle (2022), “Is Distance Really Dead in the Online World? The Moderating Role of Geographical Distance on the Effectiveness of Electronic Word of Mouth,” Journal of Marketing, 86 (4), 118–40.
44.
TopalogluOmerDassMayukh (2021), “The Impact of Online Review Content and Linguistic Style Matching on New Product Sales: The Moderating Role of Review Helpfulness,” Decision Sciences, 52 (3), 749–75.
45.
TübbickeStefan (2023), “ebct: Using Entropy Balancing for Continuous Treatments to Estimate Dose–Response Functions and Their Derivatives,” Stata Journal, 23 (3), 709–29.
46.
TuckerCatherine (2014), “Social Networks, Personalized Advertising, and Privacy Controls,” Journal of Marketing Research, 51 (5), 546–62.
47.
VargaMartonAlbuquerquePaulo (2024), “The Impact of Negative Reviews on Online Search and Purchase Decisions,” Journal of Marketing Research, 61 (5), 803–20.
48.
WeathersDannySwainScott D.GroverVarun (2015), “Can Online Product Reviews Be More Helpful? Examining Characteristics of Information Content by Product Type,” Decision Support Systems, 79, 12–23.
49.
WuXiaoyueJinLiyinXuQian (2021), “Expertise Makes Perfect: How the Variance of a Reviewer’s Historical Ratings Influences the Persuasiveness of Online Reviews,” Journal of Retailing, 97 (2), 238–50.
50.
YazdaniElhamGopinathShyamCarsonSteve (2018), “Preaching to the Choir: The Chasm Between Top-Ranked Reviewers, Mainstream Customers, and Product Sales,” Marketing Science, 37 (5), 838–51.
51.
YinDezhiBondSamuel D.ZhangHan (2017), “Keep Your Cool or Let It Out: Nonlinear Effects of Expressed Arousal on Perceptions of Consumer Reviews,” Journal of Marketing Research, 54 (3), 447–63.
52.
ZhangCongSinhaAtish P.WangYang (2024), “When to Target Customers for Helpful Reviews: The Evolution of Consumers’ Product Evaluations with Product Exposure,” Information Systems Frontiers, 26, 1183–99.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
